Associate Professor Pascal Duijf

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Associate Professor in Genetics and Informatics, School of Biomedical Sciences

PhD (Human Genetics) (Radboud University Nijmegen)

Dr Pascal Duijf obtained a Bachelor’s degree in Biology and a Master’s degree in Medical Biology from Radboud University Nijmegen in the Netherlands and was awarded two scholarships that enabled him to gain research experience in cell biology at Harvard Medical School in Boston, MA in the United States.

He then pursued a PhD degree in Human Molecular Genetics at Radboud University Nijmegen Medical Centre. His research established genotype-phenotype correlations for a variety of human congenital disorders that are caused by germline mutations in the TP63 gene and are characterised by developmental abnormalities of the limbs, ectodermal structures and/or lip/palate.

For his postdoctoral research, Dr Duijf moved to the United States. At Memorial Sloan-Kettering Cancer Center in New York, he studied how chromosome instability and aneuploidy contribute to cancer development and progression. Using systems approaches, his research showed that cancer cells preferentially lose small chromosomes, although, paradoxically, gains of chromosomes predict poor prognosis in ovarian cancer. In addition, his research demonstrated that chromosome instability can be rescued in a p53 mutant mouse tumour model. This was a significant observation, as it indicates that targeting chromosome instability in human tumours will be an effective strategy to treat cancer patients.

In 2013, Dr Duijf established his independent research group at the University of Queensland and the Translational Research Institute (TRI) in Brisbane, Australia. In 2019, he moved his research program to Queensland University of Technology (QUT) at the TRI. His research focuses on identifying the causes and consequences of genomic instability in the development of cancer. He aims to translate this knowledge into the development of cancer diagnostic, therapeutic and precision medicine approaches. To achieve this, he uses a broad range of methods, including mouse modelling, genome editing, microscopy, cell and molecular biology, molecular pathology, proteomics and computational systems genomics.

As a group leader in Australia, Dr Duijf’s major contributions to the research field have included:

  1. Using machine learning, a form of artificial intelligence, identification of 31 chromosome arm aneuploidies that robustly alter response to 56 chemotherapeutic drugs across cell lines representing 17 types of cancer (Shukla et al 2020, Nature Communications). This may ultimately improve precision cancer treatment.
  2. Pan-cancer identification of aneuploidies that drive tumour evolution and predict good or poor patient outcome (Shukla et al 2020, Nature Communications).
  3. Identification of genes whose overexpression promotes genomic instability and/or tumour development (e.g., Emi1COL17A1CENPIand EEF1A1) and the underlying mechanisms. PMIDs: 27065322278911932897793530224719.
  4. Identification of key genomic factors that predispose to cancerous translocations (i.e., acrocentrism and open chromatin state). PMID: 29316705.